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Record W2033623594 · doi:10.1139/x06-111

Use of amphibians to define riparian zones of headwater streams

2006· article· en· W2033623594 on OpenAlexvenueno aff
Dustin W. Perkins, M. L. Hunter

Bibliographic record

VenueCanadian Journal of Forest Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersMaine Agricultural and Forest Experiment StationNational Fish and Wildlife Foundation
KeywordsRiparian zoneSpecies richnessEcologySalamanderSTREAMSRiparian forestHabitatAbundance (ecology)AmphibianGeographyBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Riparian areas are known for their high species richness and their influence on ecological processes. However, riparian zones are difficult to define because of their ambiguous borders. Defining riparian zones by examining habitat use of species that require both terrestrial and aquatic environments is one method that has not been thoroughly examined. We sampled amphibians in Maine, USA, with pitfall traps located at five distances (1, 8, 18, 28, and 33 m) from 15 headwater streams. We captured 1897 amphibians of 10 species over 73 536 trap-nights. We used a repeated-measures analysis of variance to determine if species' capture rates varied among pitfall-trap locations. The highest numbers of three species, spring salamander (Gyrinophilus porphyriticus), two-lined salamander (Eurycea bislineata), and dusky salamander (Desmognathus fuscus), were captured in trap locations closest to the streams. Total species richness and average species richness were highest in the trap location located closest to the stream. We conclude that the riparian zone along headwater streams, as defined by amphibian species richness and abundance, is relatively narrow (7–9 m).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.279
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2006
Admission routes1
Has abstractyes

Explore more

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